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Correlated Disturbances and U.S. Business Cycles

  • Ricardo Reis

    (Columbia University)

  • Vasco Curdia

    (FRB New York)

The dynamic stochastic general equilibrium (DSGE) models used to study business cycles typically assume that exogenous disturbances are independent with a simple structure for serial correlation. This paper relaxes this tight restriction, by allowing for disturbances that have a rich contemporaneous and dynamic correlation structure. Our first contribution is a new Bayesian econometric method that uses conjugate conditionals to make the estimation of DSGE models with correlated disturbances feasible and quick. Our second contribution is a re-examination of the sources of U.S. business cycles, using two canonical models, one real and the other monetary. We find that when we allow for correlated disturbances, the estimates of crucial parameters are more in line with other evidence, the impulse responses are closer to the results from vector autoregressions, and government spending and technology disturbances play a larger role in the business cycle, while changes in markups are unimportant

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Paper provided by Society for Economic Dynamics in its series 2009 Meeting Papers with number 129.

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Date of creation: 2009
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Handle: RePEc:red:sed009:129
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